Pages that link to "Item:Q3433211"

The following pages link to Modeling Longitudinal Data with Nonignorable Dropouts Using a Latent Dropout Class Model (Q3433211):

Displaying 38 items.

• Handling attrition in longitudinal studies: the case for refreshment samples (Q252761) (← links)
• Bayesian latent pattern mixture models for handling attrition in panel studies with refreshment samples (Q288563) (← links)
• A latent transition analysis model for latent-state-dependent nonignorable missingness (Q316777) (← links)
• An analysis of longitudinal data with nonignorable dropout using the truncated multivariate normal distribution (Q406530) (← links)
• Bayesian modeling longitudinal dyadic data with nonignorable dropout, with application to a breast cancer study (Q439170) (← links)
• A latent class selection model for nonignorably missing data (Q452686) (← links)
• A hidden Markov model for informative dropout in longitudinal response data with crisis states (Q544599) (← links)
• Estimation in longitudinal studies with nonignorable dropout (Q897201) (← links)
• Nonignorable dropout models for longitudinal binary data with random effects: an application of Monte Carlo approximation through the Gibbs output (Q961962) (← links)
• Bayesian approaches for missing not at random outcome data: the role of identifying restrictions (Q1799346) (← links)
• Statistical modeling of longitudinal data with non-ignorable non-monotone missingness with semiparametric Bayesian and machine learning components (Q2040667) (← links)
• A Dirichlet process mixture model for non-ignorable dropout (Q2057350) (← links)
• An alternative sensitivity approach for longitudinal analysis with dropout (Q2272849) (← links)
• Handling non-ignorable dropouts in longitudinal data: a conditional model based on a latent Markov heterogeneity structure (Q2348716) (← links)
• Latent drop-out based transitions in linear quantile hidden Markov models for longitudinal responses with attrition (Q2418411) (← links)
• A reanalysis of a longitudinal scleroderma clinical trial using non-ignorable missingness models (Q2455407) (← links)
• Bayesian Nonparametrics for Missing Data in Longitudinal Clinical Trials (Q2800209) (← links)
• Pattern mixture models for the analysis of repeated attempt designs (Q2809550) (← links)
• Modeling Longitudinal Obesity Data with Intermittent Missingness Using a New Latent Variable Model (Q2816735) (← links)
• Selection and pattern mixture models for modelling longitudinal data with dropout: an application study (Q2920820) (← links)
• Varying-coefficient models for longitudinal processes with continuous-time informative dropout (Q3303588) (← links)
• A Two-Latent-Class Model for Smoking Cessation Data with Informative Dropouts (Q3396361) (← links)
• Latent Pattern Mixture Models for Informative Intermittent Missing Data in Longitudinal Studies (Q3442957) (← links)
• A discrete time event‐history approach to informative drop‐out in mixed latent Markov models with covariates (Q3465726) (← links)
• A General Class of Pattern Mixture Models for Nonignorable Dropout with Many Possible Dropout Times (Q3506504) (← links)
• Score Test for Conditional Independence Between Longitudinal Outcome and Time to Event Given the Classes in the Joint Latent Class Model (Q3561796) (← links)
• Mixed‐Effect Hybrid Models for Longitudinal Data with Nonignorable Dropout (Q3636993) (← links)
• Median Regression Models for Longitudinal Data with Dropouts (Q3637017) (← links)
• Protective estimation of longitudinal categorical data with nonrandom dropout (Q4337302) (← links)
• Generalized linear mixture models for handling nonignorable dropouts in longitudinal studies (Q4512445) (← links)
• A Joint Modeling Approach for Longitudinal Outcomes and Non-ignorable Dropout under Population Heterogeneity in Mental Health Studies (Q5044650) (← links)
• Comparison of maximum likelihood approach, Diggle–Kenward selection model, pattern mixture model with MAR and MNAR dropout data (Q5086316) (← links)
• Testing for qualitative interaction of multiple sources of informative dropout in longitudinal data (Q5124844) (← links)
• Joint partially linear model for longitudinal data with informative drop‐outs (Q5347404) (← links)
• Bayesian Latent‐Class Mixed‐Effect Hybrid Models for Dyadic Longitudinal Data with Non‐Ignorable Dropouts (Q5408012) (← links)
• A Hybrid Model for Nonignorable Dropout in Longitudinal Binary Responses (Q5473220) (← links)
• Spatial joint models through Bayesian structured piecewise additive joint modelling for longitudinal and time-to-event data (Q6089191) (← links)
• A shared-parameter continuous-time hidden Markov and survival model for longitudinal data with informative dropout (Q6625720) (← links)